| { |
| "cells": [ |
| { |
| "cell_type": "markdown", |
| "id": "786b5ed6", |
| "metadata": {}, |
| "source": [ |
| "## Imports used in this notebook\n", |
| "Most libraries available through Anaconda 3.8\n" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 1, |
| "id": "d124d3c4", |
| "metadata": {}, |
| "outputs": [], |
| "source": [ |
| "from elasticsearch import Elasticsearch\n", |
| "from elasticsearch_dsl import connections\n", |
| "from elasticsearch_dsl import Search\n", |
| "from elasticsearch_dsl import Q\n", |
| "from elasticsearch_dsl.query import MultiMatch, Match\n", |
| "from collections import Counter, deque\n", |
| "from itertools import count\n", |
| "from uuid import uuid4\n", |
| "\n", |
| "import sys\n", |
| "sys.path.append('../')\n", |
| "\n", |
| "import datetime\n", |
| "import distill\n", |
| "import numpy as np\n", |
| "import pandas as pd\n", |
| "from pandas.io.json import json_normalize\n", |
| "import plotly.express as px\n", |
| "import json\n", |
| "import itertools\n", |
| "import os\n", |
| "import networkx as nx\n", |
| "import hashlib, base64\n", |
| "import plotly.graph_objects as go" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "id": "0b993083", |
| "metadata": {}, |
| "source": [ |
| "## Create the Connection, Define Searches, and Create Generator" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 54, |
| "id": "b33ba803", |
| "metadata": {}, |
| "outputs": [], |
| "source": [ |
| "flagonClient = connections.create_connection('flagonTest', hosts=['localhost:9200'], timeout=60)\n", |
| "AleS = Search(using='flagonTest', index=\"userale\")\n", |
| "#Filtering raw and custom logs only\n", |
| "qLogType = Q(\"match\", logType=\"raw\") | Q(\"match\", logType=\"custom\")\n", |
| "#defining the user\n", |
| "qUserId = Q(\"match\", userId=\"nobody\")\n", |
| "#Filtering sessionID\n", |
| "qExcludeSession = Q(\"match\", sessionID=\"session_1671327289682\")\n", |
| "#session_1671327289682\n", |
| "#Querying through superset dashboard logs only\n", |
| "qUrl = Q({\"wildcard\": {\n", |
| " \"pageUrl\": {\n", |
| " \"value\": \"*/superset/dashboard*\"\n", |
| " }\n", |
| "}})" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 55, |
| "id": "7981a363", |
| "metadata": {}, |
| "outputs": [], |
| "source": [ |
| "elk_search = AleS \\\n", |
| " .query(qUrl) \\\n", |
| " .query(qLogType) \\\n", |
| " .query(qUserId) \\\n", |
| " .query(qExcludeSession) \\\n", |
| " .extra(track_total_hits=True) #breaks return limit of 10000 hits" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 56, |
| "id": "5d5abd92", |
| "metadata": {}, |
| "outputs": [ |
| { |
| "data": { |
| "text/plain": [ |
| "187" |
| ] |
| }, |
| "execution_count": 56, |
| "metadata": {}, |
| "output_type": "execute_result" |
| } |
| ], |
| "source": [ |
| "ale_dict = {}\n", |
| "elk_response = elk_search.scan()\n", |
| "for hit in elk_response:\n", |
| " logEntry = (hit.to_dict())\n", |
| " logEntry['uid'] = distill.getUUID(logEntry)\n", |
| " logEntry['clientTime'] = distill.epoch_to_datetime(logEntry['clientTime'])\n", |
| " ctr = len(ale_dict)\n", |
| " ctr += 1\n", |
| " ale_dict[ctr] = logEntry\n", |
| "sorted_data = dict(sorted(ale_dict.items(), key = lambda kv: kv[1]['clientTime']))\n", |
| "len(sorted_data)" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "id": "03b6a6ff", |
| "metadata": {}, |
| "source": [ |
| "# Filter Dictionaries" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "id": "293b32dc", |
| "metadata": {}, |
| "source": [ |
| "Getting a count of how many of the logs included `path`" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 57, |
| "id": "33463560", |
| "metadata": {}, |
| "outputs": [ |
| { |
| "data": { |
| "text/plain": [ |
| "187" |
| ] |
| }, |
| "execution_count": 57, |
| "metadata": {}, |
| "output_type": "execute_result" |
| } |
| ], |
| "source": [ |
| "values = ['path']\n", |
| "sorted_data_paths = {k:v for k, v in sorted_data.items() if any(item in values for item in v.keys())}\n", |
| "len(sorted_data_paths)" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "id": "044366f1", |
| "metadata": {}, |
| "source": [ |
| "# Segmentation - Create the Segment object" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 135, |
| "id": "2d8e5c63", |
| "metadata": {}, |
| "outputs": [], |
| "source": [ |
| "superSegments = distill.Segments([])\n" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "id": "48ac1c47", |
| "metadata": {}, |
| "source": [ |
| "Creating the `deadSpaceSegments`, which are segments that do not include logs" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 136, |
| "id": "0b90ca22", |
| "metadata": {}, |
| "outputs": [ |
| { |
| "name": "stdout", |
| "output_type": "stream", |
| "text": [ |
| "deadSpace1 Segment_Type.DEADSPACE (1671327545675, 1671327656414) 110.739 2 [42, 71]\n", |
| "deadSpace2 Segment_Type.DEADSPACE (1671327737051, 1671331598676) 3861.625 2 [118, 120]\n", |
| "deadSpace3 Segment_Type.DEADSPACE (1671331599808, 1671369695537) 38095.729 2 [121, 124]\n", |
| "deadSpace4 Segment_Type.DEADSPACE (1671369766609, 1671370107160) 340.551 2 [186, 187]\n" |
| ] |
| } |
| ], |
| "source": [ |
| "deadSpaceSegments = distill.detect_deadspace(sorted_data_paths, 60, 0, 0)\n", |
| "for counter, d in enumerate(deadSpaceSegments, start=1):\n", |
| " d.segment_name = str(\"deadSpace\" + str(counter)) #renaming segment names on the fly\n", |
| " d.segment_length_sec = (d.start_end_val[1] - d.start_end_val[0])/1000 #adding custom segment-object attributes\n", |
| " print(d.segment_name, d.segment_type, d.start_end_val, d.segment_length_sec, d.num_logs, d.uids)" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "id": "db845b10", |
| "metadata": {}, |
| "source": [ |
| "Creating the `mapSegments`, which are segments that include the world map in their path" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 137, |
| "id": "0aee20fb", |
| "metadata": {}, |
| "outputs": [ |
| { |
| "name": "stdout", |
| "output_type": "stream", |
| "text": [ |
| "map_1 (1671327518015, 1671327548015) 30.0 65\n", |
| "map_2 (1671327656414, 1671327686414) 30.0 52\n", |
| "map_3 (1671327737051, 1671327767051) 30.0 1\n", |
| "map_4 (1671331598676, 1671331628676) 30.0 2\n", |
| "map_5 (1671369695537, 1671369725537) 30.0 21\n", |
| "map_6 (1671369733851, 1671369763851) 30.0 38\n", |
| "map_7 (1671369766609, 1671369796609) 30.0 1\n" |
| ] |
| } |
| ], |
| "source": [ |
| "mapSegments = distill.generate_segments(sorted_data_paths,'path',['div.superset-legacy-chart-world-map','window'],0,30)\n", |
| "for counter, d in enumerate(mapSegments, start=1): \n", |
| " d.segment_name = str(\"map_\" + str(counter))\n", |
| " d.segment_length_sec = (d.start_end_val[1] - d.start_end_val[0])/1000 #adding custom segment-object attributes\n", |
| " print(d.segment_name, d.start_end_val, d.segment_length_sec, d.num_logs)\n", |
| "for d in mapSegments:\n", |
| " if d.num_logs > 20:\n", |
| " superSegments.append(d)" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "id": "1a01eeb7", |
| "metadata": {}, |
| "source": [ |
| "Append the `DeadSpaceSegments` and `mapSegments` to `superSegments`" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 138, |
| "id": "13f3719e", |
| "metadata": {}, |
| "outputs": [ |
| { |
| "name": "stdout", |
| "output_type": "stream", |
| "text": [ |
| "map_1 Segment_Type.GENERATE\n", |
| "map_2 Segment_Type.GENERATE\n", |
| "map_5 Segment_Type.GENERATE\n", |
| "map_6 Segment_Type.GENERATE\n", |
| "deadSpace1 Segment_Type.DEADSPACE\n", |
| "deadSpace2 Segment_Type.DEADSPACE\n", |
| "deadSpace3 Segment_Type.DEADSPACE\n", |
| "deadSpace4 Segment_Type.DEADSPACE\n" |
| ] |
| } |
| ], |
| "source": [ |
| "mapSegments_list = []\n", |
| "mapSegment_times = []\n", |
| "for d in mapSegments:\n", |
| " if d.num_logs > 0:\n", |
| " mapSegments_list.append(d.segment_name)\n", |
| " mapSegment_times.append(d.start_end_val)\n", |
| " \n", |
| "for i in deadSpaceSegments:\n", |
| " superSegments.append(i)\n", |
| "\n", |
| "for d in superSegments:\n", |
| " print(d.segment_name, d.segment_type)" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "id": "a63a9ea8", |
| "metadata": {}, |
| "source": [ |
| "Filter out segments that have less than 20 logs" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 139, |
| "id": "a3277271", |
| "metadata": {}, |
| "outputs": [ |
| { |
| "name": "stdout", |
| "output_type": "stream", |
| "text": [ |
| "map_1 65\n", |
| "map_2 52\n", |
| "map_5 21\n", |
| "map_6 38\n" |
| ] |
| } |
| ], |
| "source": [ |
| "mapSegments_data = distill.write_segment(sorted_data_paths, mapSegments_list, mapSegment_times)\n", |
| "for d in mapSegments_data.keys():\n", |
| " if len(mapSegments_data[d]) > 20:\n", |
| " print(d, len(mapSegments_data[d]))" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "id": "4b0e9c14", |
| "metadata": {}, |
| "source": [ |
| "## Visualizations" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 140, |
| "id": "b46988c7", |
| "metadata": {}, |
| "outputs": [], |
| "source": [ |
| "def display_segments(segments):\n", |
| " \"\"\"\n", |
| " Displays a Plotly timeline of Segment objects.\n", |
| "\n", |
| " :param segments: A Segments object containing the Segment objects to display.\n", |
| " \"\"\"\n", |
| " segment_list = []\n", |
| " for segment in segments:\n", |
| " if not isinstance(segment.start_end_val[0], datetime.datetime) or not isinstance(segment.start_end_val[1], datetime.datetime):\n", |
| " new_segment = distill.Segment()\n", |
| " new_segment.segment_name = segment.segment_name\n", |
| " new_segment.num_logs = segment.num_logs\n", |
| " new_segment.uids = segment.uids\n", |
| " new_segment.generate_field_name = segment.generate_field_name\n", |
| " new_segment.generate_matched_values = segment.generate_matched_values\n", |
| " new_segment.segment_type = segment.segment_type\n", |
| " new_segment.start_end_val = (pd.to_datetime(segment.start_end_val[0], unit='ms', origin='unix'), pd.to_datetime(segment.start_end_val[1], unit='ms', origin='unix'))\n", |
| " segment_list.append(new_segment)\n", |
| " else:\n", |
| " segment_list.append(segment)\n", |
| " new_segments = distill.Segments(segments=segment_list)\n", |
| " distill.export_segments(\"./test.csv\",new_segments)\n", |
| " df = pd.read_csv(\"./test.csv\")\n", |
| " fig = px.timeline(df, x_start=\"Start Time\", x_end=\"End Time\", y=\"Segment Name\", color=\"Number of Logs\")\n", |
| " fig.update_yaxes(autorange=\"reversed\")\n", |
| " os.remove(\"./test.csv\")\n", |
| " fig.show()" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 119, |
| "id": "88c622c4", |
| "metadata": { |
| "scrolled": false |
| }, |
| "outputs": [ |
| { |
| "data": { |
| "application/vnd.plotly.v1+json": { |
| "config": { |
| "plotlyServerURL": "https://plot.ly" |
| }, |
| "data": [ |
| { |
| "alignmentgroup": "True", |
| "base": [ |
| "2022-12-18 01:38:38.015000", |
| "2022-12-18 01:40:56.414000", |
| "2022-12-18 13:21:35.537000", |
| "2022-12-18 13:22:13.851000", |
| "2022-12-18 01:39:05.675000", |
| "2022-12-18 01:42:17.051000", |
| "2022-12-18 02:46:39.808000", |
| "2022-12-18 13:22:46.609000" |
| ], |
| "hovertemplate": "Start Time=%{base}<br>End Time=%{x}<br>Segment Name=%{y}<br>Number of Logs=%{marker.color}<extra></extra>", |
| "legendgroup": "", |
| "marker": { |
| "color": [ |
| 65, |
| 52, |
| 21, |
| 38, |
| 2, |
| 2, |
| 2, |
| 2 |
| ], |
| "coloraxis": "coloraxis", |
| "pattern": { |
| "shape": "" |
| } |
| }, |
| "name": "", |
| "offsetgroup": "", |
| "orientation": "h", |
| "showlegend": false, |
| "textposition": "auto", |
| "type": "bar", |
| "x": [ |
| 30000, |
| 30000, |
| 30000, |
| 30000, |
| 110739, |
| 3861625, |
| 38095729, |
| 340551 |
| ], |
| "xaxis": "x", |
| "y": [ |
| "map_1", |
| "map_2", |
| "map_5", |
| "map_6", |
| "deadSpace1", |
| "deadSpace2", |
| "deadSpace3", |
| "deadSpace4" |
| ], |
| "yaxis": "y" |
| } |
| ], |
| "layout": { |
| "barmode": "overlay", |
| "coloraxis": { |
| "colorbar": { |
| "title": { |
| "text": "Number of Logs" |
| } |
| }, |
| "colorscale": [ |
| [ |
| 0, |
| "#0d0887" |
| ], |
| [ |
| 0.1111111111111111, |
| "#46039f" |
| ], |
| [ |
| 0.2222222222222222, |
| "#7201a8" |
| ], |
| [ |
| 0.3333333333333333, |
| "#9c179e" |
| ], |
| [ |
| 0.4444444444444444, |
| "#bd3786" |
| ], |
| [ |
| 0.5555555555555556, |
| "#d8576b" |
| ], |
| [ |
| 0.6666666666666666, |
| "#ed7953" |
| ], |
| [ |
| 0.7777777777777778, |
| "#fb9f3a" |
| ], |
| [ |
| 0.8888888888888888, |
| "#fdca26" |
| ], |
| [ |
| 1, |
| "#f0f921" |
| ] |
| ] |
| }, |
| "legend": { |
| "tracegroupgap": 0 |
| }, |
| "margin": { |
| "t": 60 |
| }, |
| "template": { |
| "data": { |
| "bar": [ |
| { |
| "error_x": { |
| "color": "#2a3f5f" |
| }, |
| "error_y": { |
| "color": "#2a3f5f" |
| }, |
| "marker": { |
| "line": { |
| "color": "#E5ECF6", |
| "width": 0.5 |
| }, |
| "pattern": { |
| "fillmode": "overlay", |
| "size": 10, |
| "solidity": 0.2 |
| } |
| }, |
| "type": "bar" |
| } |
| ], |
| "barpolar": [ |
| { |
| "marker": { |
| "line": { |
| "color": "#E5ECF6", |
| "width": 0.5 |
| }, |
| "pattern": { |
| "fillmode": "overlay", |
| "size": 10, |
| "solidity": 0.2 |
| } |
| }, |
| "type": "barpolar" |
| } |
| ], |
| "carpet": [ |
| { |
| "aaxis": { |
| "endlinecolor": "#2a3f5f", |
| "gridcolor": "white", |
| "linecolor": "white", |
| "minorgridcolor": "white", |
| "startlinecolor": "#2a3f5f" |
| }, |
| "baxis": { |
| "endlinecolor": "#2a3f5f", |
| "gridcolor": "white", |
| "linecolor": "white", |
| "minorgridcolor": "white", |
| "startlinecolor": "#2a3f5f" |
| }, |
| "type": "carpet" |
| } |
| ], |
| "choropleth": [ |
| { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| }, |
| "type": "choropleth" |
| } |
| ], |
| "contour": [ |
| { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| }, |
| "colorscale": [ |
| [ |
| 0, |
| "#0d0887" |
| ], |
| [ |
| 0.1111111111111111, |
| "#46039f" |
| ], |
| [ |
| 0.2222222222222222, |
| "#7201a8" |
| ], |
| [ |
| 0.3333333333333333, |
| "#9c179e" |
| ], |
| [ |
| 0.4444444444444444, |
| "#bd3786" |
| ], |
| [ |
| 0.5555555555555556, |
| "#d8576b" |
| ], |
| [ |
| 0.6666666666666666, |
| "#ed7953" |
| ], |
| [ |
| 0.7777777777777778, |
| "#fb9f3a" |
| ], |
| [ |
| 0.8888888888888888, |
| "#fdca26" |
| ], |
| [ |
| 1, |
| "#f0f921" |
| ] |
| ], |
| "type": "contour" |
| } |
| ], |
| "contourcarpet": [ |
| { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| }, |
| "type": "contourcarpet" |
| } |
| ], |
| "heatmap": [ |
| { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| }, |
| "colorscale": [ |
| [ |
| 0, |
| "#0d0887" |
| ], |
| [ |
| 0.1111111111111111, |
| "#46039f" |
| ], |
| [ |
| 0.2222222222222222, |
| "#7201a8" |
| ], |
| [ |
| 0.3333333333333333, |
| "#9c179e" |
| ], |
| [ |
| 0.4444444444444444, |
| "#bd3786" |
| ], |
| [ |
| 0.5555555555555556, |
| "#d8576b" |
| ], |
| [ |
| 0.6666666666666666, |
| "#ed7953" |
| ], |
| [ |
| 0.7777777777777778, |
| "#fb9f3a" |
| ], |
| [ |
| 0.8888888888888888, |
| "#fdca26" |
| ], |
| [ |
| 1, |
| "#f0f921" |
| ] |
| ], |
| "type": "heatmap" |
| } |
| ], |
| "heatmapgl": [ |
| { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| }, |
| "colorscale": [ |
| [ |
| 0, |
| "#0d0887" |
| ], |
| [ |
| 0.1111111111111111, |
| "#46039f" |
| ], |
| [ |
| 0.2222222222222222, |
| "#7201a8" |
| ], |
| [ |
| 0.3333333333333333, |
| "#9c179e" |
| ], |
| [ |
| 0.4444444444444444, |
| "#bd3786" |
| ], |
| [ |
| 0.5555555555555556, |
| "#d8576b" |
| ], |
| [ |
| 0.6666666666666666, |
| "#ed7953" |
| ], |
| [ |
| 0.7777777777777778, |
| "#fb9f3a" |
| ], |
| [ |
| 0.8888888888888888, |
| "#fdca26" |
| ], |
| [ |
| 1, |
| "#f0f921" |
| ] |
| ], |
| "type": "heatmapgl" |
| } |
| ], |
| "histogram": [ |
| { |
| "marker": { |
| "pattern": { |
| "fillmode": "overlay", |
| "size": 10, |
| "solidity": 0.2 |
| } |
| }, |
| "type": "histogram" |
| } |
| ], |
| "histogram2d": [ |
| { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| }, |
| "colorscale": [ |
| [ |
| 0, |
| "#0d0887" |
| ], |
| [ |
| 0.1111111111111111, |
| "#46039f" |
| ], |
| [ |
| 0.2222222222222222, |
| "#7201a8" |
| ], |
| [ |
| 0.3333333333333333, |
| "#9c179e" |
| ], |
| [ |
| 0.4444444444444444, |
| "#bd3786" |
| ], |
| [ |
| 0.5555555555555556, |
| "#d8576b" |
| ], |
| [ |
| 0.6666666666666666, |
| "#ed7953" |
| ], |
| [ |
| 0.7777777777777778, |
| "#fb9f3a" |
| ], |
| [ |
| 0.8888888888888888, |
| "#fdca26" |
| ], |
| [ |
| 1, |
| "#f0f921" |
| ] |
| ], |
| "type": "histogram2d" |
| } |
| ], |
| "histogram2dcontour": [ |
| { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| }, |
| "colorscale": [ |
| [ |
| 0, |
| "#0d0887" |
| ], |
| [ |
| 0.1111111111111111, |
| "#46039f" |
| ], |
| [ |
| 0.2222222222222222, |
| "#7201a8" |
| ], |
| [ |
| 0.3333333333333333, |
| "#9c179e" |
| ], |
| [ |
| 0.4444444444444444, |
| "#bd3786" |
| ], |
| [ |
| 0.5555555555555556, |
| "#d8576b" |
| ], |
| [ |
| 0.6666666666666666, |
| "#ed7953" |
| ], |
| [ |
| 0.7777777777777778, |
| "#fb9f3a" |
| ], |
| [ |
| 0.8888888888888888, |
| "#fdca26" |
| ], |
| [ |
| 1, |
| "#f0f921" |
| ] |
| ], |
| "type": "histogram2dcontour" |
| } |
| ], |
| "mesh3d": [ |
| { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| }, |
| "type": "mesh3d" |
| } |
| ], |
| "parcoords": [ |
| { |
| "line": { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| } |
| }, |
| "type": "parcoords" |
| } |
| ], |
| "pie": [ |
| { |
| "automargin": true, |
| "type": "pie" |
| } |
| ], |
| "scatter": [ |
| { |
| "fillpattern": { |
| "fillmode": "overlay", |
| "size": 10, |
| "solidity": 0.2 |
| }, |
| "type": "scatter" |
| } |
| ], |
| "scatter3d": [ |
| { |
| "line": { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| } |
| }, |
| "marker": { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| } |
| }, |
| "type": "scatter3d" |
| } |
| ], |
| "scattercarpet": [ |
| { |
| "marker": { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| } |
| }, |
| "type": "scattercarpet" |
| } |
| ], |
| "scattergeo": [ |
| { |
| "marker": { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| } |
| }, |
| "type": "scattergeo" |
| } |
| ], |
| "scattergl": [ |
| { |
| "marker": { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| } |
| }, |
| "type": "scattergl" |
| } |
| ], |
| "scattermapbox": [ |
| { |
| "marker": { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| } |
| }, |
| "type": "scattermapbox" |
| } |
| ], |
| "scatterpolar": [ |
| { |
| "marker": { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| } |
| }, |
| "type": "scatterpolar" |
| } |
| ], |
| "scatterpolargl": [ |
| { |
| "marker": { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| } |
| }, |
| "type": "scatterpolargl" |
| } |
| ], |
| "scatterternary": [ |
| { |
| "marker": { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| } |
| }, |
| "type": "scatterternary" |
| } |
| ], |
| "surface": [ |
| { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| }, |
| "colorscale": [ |
| [ |
| 0, |
| "#0d0887" |
| ], |
| [ |
| 0.1111111111111111, |
| "#46039f" |
| ], |
| [ |
| 0.2222222222222222, |
| "#7201a8" |
| ], |
| [ |
| 0.3333333333333333, |
| "#9c179e" |
| ], |
| [ |
| 0.4444444444444444, |
| "#bd3786" |
| ], |
| [ |
| 0.5555555555555556, |
| "#d8576b" |
| ], |
| [ |
| 0.6666666666666666, |
| "#ed7953" |
| ], |
| [ |
| 0.7777777777777778, |
| "#fb9f3a" |
| ], |
| [ |
| 0.8888888888888888, |
| "#fdca26" |
| ], |
| [ |
| 1, |
| "#f0f921" |
| ] |
| ], |
| "type": "surface" |
| } |
| ], |
| "table": [ |
| { |
| "cells": { |
| "fill": { |
| "color": "#EBF0F8" |
| }, |
| "line": { |
| "color": "white" |
| } |
| }, |
| "header": { |
| "fill": { |
| "color": "#C8D4E3" |
| }, |
| "line": { |
| "color": "white" |
| } |
| }, |
| "type": "table" |
| } |
| ] |
| }, |
| "layout": { |
| "annotationdefaults": { |
| "arrowcolor": "#2a3f5f", |
| "arrowhead": 0, |
| "arrowwidth": 1 |
| }, |
| "autotypenumbers": "strict", |
| "coloraxis": { |
| "colorbar": { |
| "outlinewidth": 0, |
| "ticks": "" |
| } |
| }, |
| "colorscale": { |
| "diverging": [ |
| [ |
| 0, |
| "#8e0152" |
| ], |
| [ |
| 0.1, |
| "#c51b7d" |
| ], |
| [ |
| 0.2, |
| "#de77ae" |
| ], |
| [ |
| 0.3, |
| "#f1b6da" |
| ], |
| [ |
| 0.4, |
| "#fde0ef" |
| ], |
| [ |
| 0.5, |
| "#f7f7f7" |
| ], |
| [ |
| 0.6, |
| "#e6f5d0" |
| ], |
| [ |
| 0.7, |
| "#b8e186" |
| ], |
| [ |
| 0.8, |
| "#7fbc41" |
| ], |
| [ |
| 0.9, |
| "#4d9221" |
| ], |
| [ |
| 1, |
| "#276419" |
| ] |
| ], |
| "sequential": [ |
| [ |
| 0, |
| "#0d0887" |
| ], |
| [ |
| 0.1111111111111111, |
| "#46039f" |
| ], |
| [ |
| 0.2222222222222222, |
| "#7201a8" |
| ], |
| [ |
| 0.3333333333333333, |
| "#9c179e" |
| ], |
| [ |
| 0.4444444444444444, |
| "#bd3786" |
| ], |
| [ |
| 0.5555555555555556, |
| "#d8576b" |
| ], |
| [ |
| 0.6666666666666666, |
| "#ed7953" |
| ], |
| [ |
| 0.7777777777777778, |
| "#fb9f3a" |
| ], |
| [ |
| 0.8888888888888888, |
| "#fdca26" |
| ], |
| [ |
| 1, |
| "#f0f921" |
| ] |
| ], |
| "sequentialminus": [ |
| [ |
| 0, |
| "#0d0887" |
| ], |
| [ |
| 0.1111111111111111, |
| "#46039f" |
| ], |
| [ |
| 0.2222222222222222, |
| "#7201a8" |
| ], |
| [ |
| 0.3333333333333333, |
| "#9c179e" |
| ], |
| [ |
| 0.4444444444444444, |
| "#bd3786" |
| ], |
| [ |
| 0.5555555555555556, |
| "#d8576b" |
| ], |
| [ |
| 0.6666666666666666, |
| "#ed7953" |
| ], |
| [ |
| 0.7777777777777778, |
| "#fb9f3a" |
| ], |
| [ |
| 0.8888888888888888, |
| "#fdca26" |
| ], |
| [ |
| 1, |
| "#f0f921" |
| ] |
| ] |
| }, |
| "colorway": [ |
| "#636efa", |
| "#EF553B", |
| "#00cc96", |
| "#ab63fa", |
| "#FFA15A", |
| "#19d3f3", |
| "#FF6692", |
| "#B6E880", |
| "#FF97FF", |
| "#FECB52" |
| ], |
| "font": { |
| "color": "#2a3f5f" |
| }, |
| "geo": { |
| "bgcolor": "white", |
| "lakecolor": "white", |
| "landcolor": "#E5ECF6", |
| "showlakes": true, |
| "showland": true, |
| "subunitcolor": "white" |
| }, |
| "hoverlabel": { |
| "align": "left" |
| }, |
| "hovermode": "closest", |
| "mapbox": { |
| "style": "light" |
| }, |
| "paper_bgcolor": "white", |
| "plot_bgcolor": "#E5ECF6", |
| "polar": { |
| "angularaxis": { |
| "gridcolor": "white", |
| "linecolor": "white", |
| "ticks": "" |
| }, |
| "bgcolor": "#E5ECF6", |
| "radialaxis": { |
| "gridcolor": "white", |
| "linecolor": "white", |
| "ticks": "" |
| } |
| }, |
| "scene": { |
| "xaxis": { |
| "backgroundcolor": "#E5ECF6", |
| "gridcolor": "white", |
| "gridwidth": 2, |
| "linecolor": "white", |
| "showbackground": true, |
| "ticks": "", |
| "zerolinecolor": "white" |
| }, |
| "yaxis": { |
| "backgroundcolor": "#E5ECF6", |
| "gridcolor": "white", |
| "gridwidth": 2, |
| "linecolor": "white", |
| "showbackground": true, |
| "ticks": "", |
| "zerolinecolor": "white" |
| }, |
| "zaxis": { |
| "backgroundcolor": "#E5ECF6", |
| "gridcolor": "white", |
| "gridwidth": 2, |
| "linecolor": "white", |
| "showbackground": true, |
| "ticks": "", |
| "zerolinecolor": "white" |
| } |
| }, |
| "shapedefaults": { |
| "line": { |
| "color": "#2a3f5f" |
| } |
| }, |
| "ternary": { |
| "aaxis": { |
| "gridcolor": "white", |
| "linecolor": "white", |
| "ticks": "" |
| }, |
| "baxis": { |
| "gridcolor": "white", |
| "linecolor": "white", |
| "ticks": "" |
| }, |
| "bgcolor": "#E5ECF6", |
| "caxis": { |
| "gridcolor": "white", |
| "linecolor": "white", |
| "ticks": "" |
| } |
| }, |
| "title": { |
| "x": 0.05 |
| }, |
| "xaxis": { |
| "automargin": true, |
| "gridcolor": "white", |
| "linecolor": "white", |
| "ticks": "", |
| "title": { |
| "standoff": 15 |
| }, |
| "zerolinecolor": "white", |
| "zerolinewidth": 2 |
| }, |
| "yaxis": { |
| "automargin": true, |
| "gridcolor": "white", |
| "linecolor": "white", |
| "ticks": "", |
| "title": { |
| "standoff": 15 |
| }, |
| "zerolinecolor": "white", |
| "zerolinewidth": 2 |
| } |
| } |
| }, |
| "xaxis": { |
| "anchor": "y", |
| "domain": [ |
| 0, |
| 1 |
| ], |
| "type": "date" |
| }, |
| "yaxis": { |
| "anchor": "x", |
| "autorange": "reversed", |
| "domain": [ |
| 0, |
| 1 |
| ], |
| "title": { |
| "text": "Segment Name" |
| } |
| } |
| } |
| }, |
| "text/html": [ |
| "<div> <div id=\"bfea3054-9f50-4c70-bc65-ae43d1fef4e4\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"bfea3054-9f50-4c70-bc65-ae43d1fef4e4\")) { Plotly.newPlot( \"bfea3054-9f50-4c70-bc65-ae43d1fef4e4\", [{\"alignmentgroup\":\"True\",\"base\":[\"2022-12-18 01:38:38.015000\",\"2022-12-18 01:40:56.414000\",\"2022-12-18 13:21:35.537000\",\"2022-12-18 13:22:13.851000\",\"2022-12-18 01:39:05.675000\",\"2022-12-18 01:42:17.051000\",\"2022-12-18 02:46:39.808000\",\"2022-12-18 13:22:46.609000\"],\"hovertemplate\":\"Start Time=%{base}<br>End Time=%{x}<br>Segment Name=%{y}<br>Number of Logs=%{marker.color}<extra></extra>\",\"legendgroup\":\"\",\"marker\":{\"color\":[65,52,21,38,2,2,2,2],\"coloraxis\":\"coloraxis\",\"pattern\":{\"shape\":\"\"}},\"name\":\"\",\"offsetgroup\":\"\",\"orientation\":\"h\",\"showlegend\":false,\"textposition\":\"auto\",\"x\":[30000.0,30000.0,30000.0,30000.0,110739.0,3861625.0,38095729.0,340551.0],\"xaxis\":\"x\",\"y\":[\"map_1\",\"map_2\",\"map_5\",\"map_6\",\"deadSpace1\",\"deadSpace2\",\"deadSpace3\",\"deadSpace4\"],\"yaxis\":\"y\",\"type\":\"bar\"}], {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmapgl\":[{\"type\":\"heatmapgl\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermapbox\":[{\"type\":\"scattermapbox\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05},\"mapbox\":{\"style\":\"light\"}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"type\":\"date\"},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Segment Name\"},\"autorange\":\"reversed\"},\"coloraxis\":{\"colorbar\":{\"title\":{\"text\":\"Number of Logs\"}},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"legend\":{\"tracegroupgap\":0},\"margin\":{\"t\":60},\"barmode\":\"overlay\"}, {\"responsive\": true} ).then(function(){\n", |
| " \n", |
| "var gd = document.getElementById('bfea3054-9f50-4c70-bc65-ae43d1fef4e4');\n", |
| "var x = new MutationObserver(function (mutations, observer) {{\n", |
| " var display = window.getComputedStyle(gd).display;\n", |
| " if (!display || display === 'none') {{\n", |
| " console.log([gd, 'removed!']);\n", |
| " Plotly.purge(gd);\n", |
| " observer.disconnect();\n", |
| " }}\n", |
| "}});\n", |
| "\n", |
| "// Listen for the removal of the full notebook cells\n", |
| "var notebookContainer = gd.closest('#notebook-container');\n", |
| "if (notebookContainer) {{\n", |
| " x.observe(notebookContainer, {childList: true});\n", |
| "}}\n", |
| "\n", |
| "// Listen for the clearing of the current output cell\n", |
| "var outputEl = gd.closest('.output');\n", |
| "if (outputEl) {{\n", |
| " x.observe(outputEl, {childList: true});\n", |
| "}}\n", |
| "\n", |
| " }) }; }); </script> </div>" |
| ] |
| }, |
| "metadata": {}, |
| "output_type": "display_data" |
| } |
| ], |
| "source": [ |
| "display_segments(superSegments)" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "id": "747a0c84", |
| "metadata": {}, |
| "source": [ |
| "Create the edges and nodes for the graphs" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 127, |
| "id": "160787a2", |
| "metadata": {}, |
| "outputs": [], |
| "source": [ |
| "edges_map_1 = distill.pairwiseSeq(['|'.join(log['path']) for log in mapSegments_data['map_1'].values()])\n", |
| "edges_list_map_1 = list(edges_map_1)\n", |
| "edges_map_2 = distill.pairwiseSeq(['|'.join(log['path']) for log in mapSegments_data['map_6'].values()])\n", |
| "edges_list_map_2 = list(edges_map_2)\n", |
| "\n", |
| "nodes_map_1 = set(['|'.join(log['path']) for log in mapSegments_data['map_1'].values()])\n", |
| "nodes_list_map_1 = list(nodes_map_1)\n", |
| "nodes_map_2 = set(['|'.join(log['path']) for log in mapSegments_data['map_6'].values()])\n", |
| "nodes_list_map_2 = list(nodes_map_2)\n", |
| "\n", |
| "G_map1 = distill.createDiGraph(nodes_list_map_1, edges_list_map_1, drop_recursions = False)\n", |
| "G_map2 = distill.createDiGraph(nodes_list_map_2, edges_list_map_2, drop_recursions = False)" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 142, |
| "id": "ae21a3ea", |
| "metadata": {}, |
| "outputs": [ |
| { |
| "data": { |
| "image/png": "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\n", |
| "text/plain": [ |
| "<Figure size 640x480 with 1 Axes>" |
| ] |
| }, |
| "metadata": {}, |
| "output_type": "display_data" |
| } |
| ], |
| "source": [ |
| "nx.draw(G_map1, with_labels=False)" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 128, |
| "id": "bf4fbae5", |
| "metadata": {}, |
| "outputs": [ |
| { |
| "data": { |
| "image/png": "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\n", |
| "text/plain": [ |
| "<Figure size 640x480 with 1 Axes>" |
| ] |
| }, |
| "metadata": {}, |
| "output_type": "display_data" |
| } |
| ], |
| "source": [ |
| "nx.draw(G_map2, with_labels=False)" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 143, |
| "id": "d741782f", |
| "metadata": {}, |
| "outputs": [ |
| { |
| "data": { |
| "text/plain": [ |
| "1.0058479532163742" |
| ] |
| }, |
| "execution_count": 143, |
| "metadata": {}, |
| "output_type": "execute_result" |
| } |
| ], |
| "source": [ |
| "nx.average_node_connectivity(G_map1)" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 144, |
| "id": "762a8f41", |
| "metadata": {}, |
| "outputs": [ |
| { |
| "data": { |
| "text/plain": [ |
| "0.7867647058823529" |
| ] |
| }, |
| "execution_count": 144, |
| "metadata": {}, |
| "output_type": "execute_result" |
| } |
| ], |
| "source": [ |
| "nx.average_node_connectivity(G_map2)" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "id": "8a4869b1", |
| "metadata": {}, |
| "source": [ |
| "How many operations are needed to get the two graphs to be identical?" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 146, |
| "id": "12c10346", |
| "metadata": {}, |
| "outputs": [ |
| { |
| "data": { |
| "text/plain": [ |
| "42.0" |
| ] |
| }, |
| "execution_count": 146, |
| "metadata": {}, |
| "output_type": "execute_result" |
| } |
| ], |
| "source": [ |
| "next(nx.optimize_graph_edit_distance(G_map1, G_map2))" |
| ] |
| } |
| ], |
| "metadata": { |
| "kernelspec": { |
| "display_name": "Python 3 (ipykernel)", |
| "language": "python", |
| "name": "python3" |
| }, |
| "language_info": { |
| "codemirror_mode": { |
| "name": "ipython", |
| "version": 3 |
| }, |
| "file_extension": ".py", |
| "mimetype": "text/x-python", |
| "name": "python", |
| "nbconvert_exporter": "python", |
| "pygments_lexer": "ipython3", |
| "version": "3.9.13" |
| } |
| }, |
| "nbformat": 4, |
| "nbformat_minor": 5 |
| } |
